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Hierarchical clustering is a method that groups similar data points into a hierarchical structure of clusters. There are two main approaches: agglomerative clustering builds clusters from the bottom up by successively merging smaller clusters, while divisive clustering splits clusters from the top down by successively dividing larger clusters. K-nearest neighbors (KNN) is an algorithm that classifies data points based on the classes of its K nearest neighbors, where increasing K reduces noise but may overge

Author

Shivansh Mishra

Language

EN